Location: US-Remote 

(AL,AZ,CA,CO,CT,DC,FL,GA,ID,IL,IN,MA,MD,MI,MO,NC,NH,NJ,NV,NY,OH,PA,RI,TN,TX,UT,VA,WA,WI)

Type: Full-Time, Salary, Exempt

About DMS

Digital Media Solutions (DMS) is a performance-driven digital marketing company that connects consumers and brands through data, technology, and proprietary media platforms. Our systems power high-volume consumer acquisition across multiple verticals, processing large-scale traffic and real-time decisioning in dynamic market environments.

About this role

We’re looking for a Business Intelligence Analyst to help build and maintain our Single source of truth for signal activity and revenue performance. In this role, you’ll work with large-scale datasets across AWS and DataBricks, transforming complex signal data into clear insights through Looker dashboards that track signal volume, API performance, and customer activity. You’ll collaborate closely with Finance, Technology, and Business teams to ensure our data is reliable and translated into insights that support product performance, revenue visibility, and strategic decision-making.

Why Join DMS?

At Digital Media Solutions, you’ll work with systems that process millions of high-intent consumer signals across web, email, push, and voice channels. In this role, you’ll help define and evolve the company’s Single Source of Truth for signal activity, revenue attribution, and product performance, shaping how the business measures, analyzes, and acts on its data. You’ll play a key role in defining the metrics and data models the company relies on to understand performance and drive strategic decisions.

You’ll work with large-scale datasets and modern analytics tools while partnering closely with Finance, Technology, and Business leaders to turn complex signal data into insights that guide product and revenue strategy.

If you enjoy owning core business metrics, working with high-volume event data, and building analytics that directly influence how a business operates, this role offers the opportunity to do exactly that.

Data Centralization

• Design and write complex SQL queries to aggregate signal data from DataBricks and AWS.
• Structure large-scale event data into a centralized data warehouse.

Single Source of Truth

• Build and maintain data models that define core business metrics.
• Ensure Finance, Technology, and Business teams are working from consistent and reliable data.

Reporting & Looker Visualization

• Lead the transition from legacy reporting tools to Looker.
• Develop LookML models and dashboards tracking:
  • Signal volume
  • API performance
  • Customer activity trends

Cross-Functional Analytics

• Partner with Finance to measure:
  • Unit economics
  • Margin by signal type
  • Revenue attribution
• Partner with Technology teams to monitor signal delivery and data health using AWS logs and Datadog.
• Partner with Business Units to build profitability views showing which signal channels drive the most value.

Data Governance

• Maintain data integrity across Last Activity API and Activity Signal products.
• Identify and resolve data discrepancies and latency issues before they impact reporting or billing accuracy.

Required Qualifications

Experience

• 3+ years of experience in business intelligence, data analytics, or data engineering environments.
• Experience working with large-scale datasets.

Technical Skills

• Advanced SQL with the ability to query large, complex datasets.
• Experience working in cloud data environments such as AWS and DataBricks.
• Experience building dashboards and data models in Looker (LookML) or leading a migration to Looker.
• Experience working with event-based data, API logs, or streaming data.
• Experience with SparkSQL or DataBricks Lakehouse architecture.

Analytical & Business Skills

• Ability to translate large datasets into clear business insights and performance metrics.
• Strong understanding of financial metrics such as LTV, CAC, and gross margin.
• Ability to work cross-functionally with Finance, Engineering, and business stakeholders.

Preferred Qualifications:

• Familiarity with Datadog for monitoring data pipelines and system performance.
• Experience analyzing API products, signal data, or event-driven systems.

Compensation:  The anticipated annual base salary range for this position is $120,000 - $130,000. Actual compensation may vary based on work experience, education, and skill level.